fabsig
Professor of Applied Statistics and Data Science at Lucerne University of Applied Sciences and Arts
Switzerland
Pinned Repositories
AirBnbPricePrediction
Training and Testing a Set of Machine Learning/Deep Learning Models to Predict Airbnb Prices for NYC
catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Compare_ML_HighCardinality_Categorical_Variables
Machine Learning Methods for High-Cardinality Categorical Data
Comparison_GLMM_Packages
Comparing Software Packages for Generalized Linear Mixed Effects Models (GLMMs)
CreateDummyVariablesSPSS
Create dummy variables in SPSS with Python 3 support for SPSS version 27 and latter
GPBoost
Combining tree-boosting with Gaussian process and mixed effects models
GradientNewtonBoosting
Comparing gradient and Newton boosting
KTBoost
A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.
ROC_PrecisionRecall
spate
spate: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach
fabsig's Repositories
fabsig/GPBoost
Combining tree-boosting with Gaussian process and mixed effects models
fabsig/KTBoost
A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.
fabsig/GradientNewtonBoosting
Comparing gradient and Newton boosting
fabsig/Compare_ML_HighCardinality_Categorical_Variables
Machine Learning Methods for High-Cardinality Categorical Data
fabsig/CreateDummyVariablesSPSS
Create dummy variables in SPSS with Python 3 support for SPSS version 27 and latter
fabsig/ROC_PrecisionRecall
fabsig/spate
spate: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach
fabsig/AirBnbPricePrediction
Training and Testing a Set of Machine Learning/Deep Learning Models to Predict Airbnb Prices for NYC
fabsig/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
fabsig/Comparison_GLMM_Packages
Comparing Software Packages for Generalized Linear Mixed Effects Models (GLMMs)
fabsig/glmmnet
fabsig/glmmnet_experiments_gpboost
fabsig/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
fabsig/shap
A game theoretic approach to explain the output of any machine learning model.
fabsig/spectra
A header-only C++ library for large scale eigenvalue problems
fabsig/iterativeFSA
fabsig/iterativeVL
This repository contains the R code for the simulations in the paper "Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models".
fabsig/lmmnn
fabsig/ML_models_for_extrapolation
fabsig/treeshap
Compute SHAP values for your tree-based models using the TreeSHAP algorithm